• Nuclear Engineering and Technology
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• 제34권2호
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• pp.154-164
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• 2002

Neutron cross section data on Dy-160, Dy-161, Dy-162, Dy-163 and Dy-164 were calculated and evaluated in the energy range of 1 keV to 20 MeV using a spherical optical model, statistical model and pre-equilibrium model. The energy dependent optical model potential parameters were obtained based on the recent experimental data. The width fluctuation correction in Hauser-Feshbach particle decay and the quantum mechanical approach in pre-equilibrium analysis were introduced and gave a better cross section calculation in EMPIRE-II. The total, elastic scattering and threshold reaction cross sections were evaluated and compared with the evaluated files. The model calculated (n, tot), (n, ${\gamma}$) and (n, p) cross sections were in good agreement with the experimental data in the measured energy range. The results will be applied to ENDF/B-VI for data improvement.

• Nuclear Engineering and Technology
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• 제34권4호
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• pp.370-381
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• 2002

The neutron induced nuclear data for Pr-141, Nd-143, Nd-145, Sm-147 and Sm-149 were calculated and evaluated from 10 keV to 20 MeV. The energy dependent optical model potential parameters were extracted based on the recent experimental data and applied up to 20 MeV. The s-wave strength function was calculated. Spherical optical model , statistical model in equilibrium energy, multistep direct and multistep compound model in pre-equilibrium energy and direct capture model were introduced in Empire calculation. The theoretically calculated cross sections were compared with the experimental data and the evaluated files. The model calculated total and capture cross sections were in good agreement with the reference experimental data. The capture cross sections in pre-equilibrium were enhanced in recent released Empire version. The evaluated cross section results were compiled to ENDF-6 format and will improve the ENDF/B-Vl.

• Smart Structures and Systems
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• 제17권6호
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• pp.1087-1105
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• 2016

Traffic load and volume is one of the most important physical quantities for bridge safety evaluation and maintenance strategies formulation. This paper aims to conduct the statistical analysis of traffic volume information and the multimodal modeling of gross vehicle weight (GVW) based on the monitoring data obtained from the weigh-in-motion (WIM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. A genetic algorithm (GA)-based mixture parameter estimation approach is developed for derivation of the unknown mixture parameters in mixed distribution models. The statistical analysis of one-year WIM data is firstly performed according to the vehicle type, single axle weight, and GVW. The probability density function (PDF) and cumulative distribution function (CDF) of the GVW data of selected vehicle types are then formulated by use of three kinds of finite mixed distributions (normal, lognormal and Weibull). The mixture parameters are determined by use of the proposed GA-based method. The results indicate that the stochastic properties of the GVW data acquired from the field-instrumented WIM sensors are effectively characterized by the method of finite mixture distributions in conjunction with the proposed GA-based mixture parameter identification algorithm. Moreover, it is revealed that the Weibull mixture distribution is relatively superior in modeling of the WIM data on the basis of the calculated Akaike's information criterion (AIC) values.

• Smart Structures and Systems
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• 제13권3호
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• pp.453-471
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• 2014

The fault diagnosis of rolling element bearings has drawn considerable research attention in recent years because these fundamental elements frequently suffer failures that could result in unexpected machine breakdowns. Artificial intelligence algorithms such as artificial neural networks (ANNs) and support vector machines (SVMs) have been widely investigated to identify various faults. However, as the useful life of a bearing deteriorates, identifying early bearing faults and evaluating their sizes of development are necessary for timely maintenance actions to prevent accidents. This study proposes a new two-layer structure consisting of support vector regression machines (SVRMs) to recognize bearing fault patterns and track the fault sizes. The statistical parameters used to track the fault evolutions are first extracted to condense original vibration signals into a few compact features. The extracted features are then used to train the proposed two-layer SVRMs structure. Once these parameters of the proposed two-layer SVRMs structure are determined, the features extracted from other vibration signals can be used to predict the unknown bearing health conditions. The effectiveness of the proposed method is validated by experimental datasets collected from a test rig. The results demonstrate that the proposed method is highly accurate in differentiating between fault patterns and determining their fault severities. Further, comparisons are performed to show that the proposed method is better than some existing methods.

• 대기
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• 제23권4호
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• pp.443-452
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• 2013

The original Fog Stability Index (FSI) is formulated as FSI=$2(T-T_d)+2(T-T_{850})+WS_{850}$, where $T-T_d$ is dew point deficit (temperature-dew point temperature), $T-T_{850}$ is atmospheric stability measure (temperature-temperature at 850 hPa altitude) and $WS_{850}$ is wind speed at 850 hPa altitude. As a way to improve fog prediction at Incheon International Airport (IIA), we develop the modified FSI for IIA, using the meteorological data at IIA for two years from June 2011 to May 2013, the first one year for development and the second one year for validation. The relative contribution of the three parameters of the modified FSI is 9: 1: 0, indicating that $WS_{850}$ is found to be a non-contributing factor for fog formation at IIA. The critical success index (CSI) of the modified FSI is 0.68. Further development is made to consider the fact that fogs at IIA are highly influenced by advection of moisture from the Yellow Sea. One added parameter after statistical evaluation of the several candidate parameters is the dew point deficit at a buoy over the Yellow Sea. The relative contribution of the four parameters (including the new one) of the newly developed FSI is 10: 2: 0.5: 6.4. The CSI of the new FSI is 0.50. Since the developmental period of one year is too short, the FSI should be refined more as the data are accumulated more.

• Structural Engineering and Mechanics
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• 제83권4호
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• pp.515-535
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• 2022

The strength models for fiber-reinforced polymer (FRP)-confined normal strength concrete (NC) cylinders available in the literature have been suggested based on small databases using limited variables of such structural members portraying less accuracy. The artificial neural network (ANN) is an advanced technique for precisely predicting the response of composite structures by considering a large number of parameters. The main objective of the present investigation is to develop an ANN model for the axial strength of FRP-confined NC cylinders using various parameters to give the highest accuracy of the predictions. To secure this aim, a large experimental database of 313 FRP-confined NC cylinders has been constructed from previous research investigations. An evaluation of 33 different empirical strength models has been performed using various statistical parameters (root mean squared error RMSE, mean absolute error MAE, and coefficient of determination R²) over the developed database. Then, a new ANN model using the Group Method of Data Handling (GMDH) has been proposed based on the experimental database that portrayed the highest performance as compared with the previous models with R²=0.92, RMSE=0.27, and MAE=0.33. Therefore, the suggested ANN model can accurately capture the axial strength of FRP-confined NC cylinders that can be used for the further analysis and design of such members in the construction industry.

• 한국수의병리학회지
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• 제3권2호
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• pp.87-91
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• 1999

The present study was undertaken to compare the variation on serum biochemical values by storage in the rats. Sera were prepared from 30 Sprague-Dawley rats of each sex. 5 aliquots from each serum were placed in a -80$^{\circ}C$ freezer with the exception of I aliquots which was analyzed immediately. The analysis was performed on the following months; 1, 2, 3, 6, and 12 months after freezing. The parameters measured) were aspartate aminotransferase(AST), alanine aminotransferase(ALT), alkaline phosphatase(ALP), blood urea nitrogen(BUN) creatinine(CRE), glucose(GLU), total cholesterol(TCHO), triglyceride (TG), total protein(TP), albumin(ALB), total bilirubin(TBIL), calcium(Ca$\^$＋＋/), inorganic phosphorus(IP), creatine kinase (CK), phospholipid(PL), albumin-globulin ratio(A/G), sodium(Na$\^$＋/), potassium(K$\^$＋/), and chloride(Cl$\^$－/) The statistical analysis with Repeated Measures ANOVA, did not show statistical significance in the parameters of AST, ALT, BUN, TG, CK, A/G, Na$\^$＋/ of 1 month freezed sera, in those of AST, TG, CK, K$\^$＋/) of 2 month freezed sera, in those of AST, ALT, BUN, CRE, TCHO, TP, TBIL, CK, PL, Na$\^$＋/), K$\^$＋/), Ct on month fteezed sera, in those of Cl$\^$－/ of 6 month fteezed sera, and in those of ALT, TG, ALB of 12 month freezed sera in male SD rats. On the other hand, it did not show statistical significance in the parameters of AST, ALT, ALP, BUN, GLU, TCHO, TG, TBIL, CK, PL, A/G, Na$\^$＋/ of 1 month freezed sera, in those of AST, TCHO of 2 month freezed sera, in those of AST, BUN, CRE, TCHO, TP, TBIL, CK, PL of 3 month freezed sera, in those of TCHO, IP, PL of 6 month freezed sera, and in those of ALB of 12 month freezed sera in female SD rats. On the basis of the results, although there are some statistical variations in the biochemical values of the sera, it is suggested that if sera are analysed at the same time before 12 months storage in a －80 $^{\circ}C$ freezer, the storing time does not affect the biochemical evaluation of the sera in SD rats.

• Journal of Radiation Protection and Research
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• 제48권3호
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• pp.144-152
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• 2023

Background: Color texture analysis was applied as a tool for quantitative evaluation of radiation-induced skin injuries. Materials and Methods: We prospectively selected 20 breast cancer patients who underwent whole-breast radiotherapy after breast-conserving surgery. Color images of skin surfaces for irradiated breasts were obtained by using a mobile skin analyzer. The first skin measurement was performed before the first fraction of radiotherapy, and the subsequent measurement was conducted approximately 10 days after the completion of the entire series of radiotherapy sessions. For comparison, color images of the skin surface for the unirradiated breasts were measured similarly. For each color image, six co-occurrence matrices (red-green [RG], red-blue [RB], and green-blue [GB] from color channels, red [R], green [G], blue [B] from gray channels) can be generated. Four textural features (contrast, correlation, energy, and homogeneity) were calculated for each co-occurrence matrix. Finally, several statistical analyses were used to investigate the performance of the color textural parameters to objectively evaluate the radiation-induced skin damage. Results and Discussion: For the R channel from the gray channel, the differences in the values between the irradiated and unirradiated skin were larger than those of the G and B channels. In addition, for the RG and RB channels, where R was considered in the color channel, the differences were larger than those in the GB channel. When comparing the relative values between gray and color channels, the 'contrast' values for the RG and RB channels were approximately two times greater than those for the R channel for irradiated skin. In contrast, there were no noticeable differences for unirradiated skin. Conclusion: The utilization of color texture analysis has shown promising results in evaluating the severity of skin damage caused by radiation. All textural parameters of the RG and RB co-occurrence matrices could be potential indicators of the extent of skin damage caused by radiation.

• 정보보호학회논문지
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• 제19권3호
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• pp.95-105
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• 2009

본 논문은 VoIP의 주요 보안 위협인 스팸에 대응하기 위한 목적으로 VoIP 스팸 탐지 기술의 성능평가를 위한 시뮬레이션 모델을 설계하고 있다. 성능평가 시뮬레이션 모델은 입력 데이터를 제공하는 기능과 출력 데이터를 분석하는 기능을 갖는다. 본 논문에서는 VoIP스팸 탐지 기술의 성능평가 입력 데이터를 위하여 VoIP 발신자 특성을 고려하여 네 종류의 Caller 모델을 개발하였고, 각 caller 모델은 결정된 패턴 내에서 call을 생성하게 된다. 성능평가는 SPIT (Spam over Internet Telephony) Level 결정 알고리즘을 대상으로 수행하고, 성능평가의 지표 도출을 통해 평가 알고리즘의 성능 지수를 산정한다. 성능평가 모델은 DEVS 형식론 기반으로 설계하였으며 DEVSJAVA$^{TM}$를 이용한 모델링 및 시뮬레이션을 통해 설계된 모델을 검증하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(5)
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• pp.293-296
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• 2002

In this study, the object is a development on uroflowmetry system to detect a voiding symptom conveniently in home or hospital. The hardware was composed of mechanism and system circuit part, the software was divided into firmware and PC program part. The following experiment was performed to evaluate an ability of classification and fitness. First, the following parameters was calculated in each flow curve pattern. The parameters are MFR, AFR, VOL, VT, FT, and TMF. A significant difference among parameters was examined through a statistical analysis for extracted parameters between normal and abnormal group. In the next work, the following experimentation was performed to classify the voiding symptom. Analysis of congregate rate was examined to find out classification possibility about each symptom of BPH, voiding difficulty, detrusor failure and hyperreflexia, unstable bladder. The uroflow data with the above symptom was divided into normal and abnormal group using fuzzy classifier. and that was performed appending the other group again. Fuzzy classification result using MFR and AFR was superior by 89.6 % more than grouping evaluation including VOL.